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Controlled vocabularies (CVs), i.e. a collection of predefined terms describing a modeling domain, used for the semantic annotation of data, and ontologies are used in structured data formats and databases to avoid inconsistencies in annotation, to have a unique (and preferably short) accession number and to give researchers and computer algorithms the possibility for more expressive semantic annotation of data. The Human Proteome Organization (HUPO)-Proteomics Standards Initiative (PSI) makes extensive use of ontologies/CVs in their data formats. The PSI-Mass Spectrometry (MS) CV contains all the terms used in the PSI MS-related data standards. The CV contains a logical hierarchical structure to ensure ease of maintenance and the development of software that makes use of complex semantics. The CV contains terms required for a complete description of an MS analysis pipeline used in proteomics, including sample labeling, digestion enzymes, instrumentation parts and parameters, software used for identification and quantification of peptides/proteins and the parameters and scores used to determine their significance. Owing to the range of topics covered by the CV, collaborative development across several PSI working groups, including proteomics research groups, instrument manufacturers and software vendors, was necessary. In this article, we describe the overall structure of the CV, the process by which it has been developed and is maintained and the dependencies on other ontologies. [ABSTRACT FROM AUTHOR]

The PRoteomics IDEntifications (PRIDE) database is a large public proteomics data repository, containing over 270 million mass spectra (by November 2011). PRIDE is an archival database, providing the proteomics data supporting specific scientific publications in a computationally accessible manner. While PRIDE faces rapid increases in data deposition size as well as number of depositions, the major challenge is to ensure a high quality of data depositions in the context of highly diverse proteomics work flows and data representations. Here, we describe the PRIDE curation pipeline and its practical application in quality control of complex data depositions.Database URL: http://www.ebi.ac.uk/pride/. [ABSTRACT FROM AUTHOR]